Ruoxuan Xiong

Ruoxuan Xiong

Stanford University

H-index: 12

North America-United States

About Ruoxuan Xiong

Ruoxuan Xiong, With an exceptional h-index of 12 and a recent h-index of 12 (since 2020), a distinguished researcher at Stanford University, specializes in the field of experimental design, causal inference, econometrics.

His recent articles reflect a diverse array of research interests and contributions to the field:

Contrastive balancing representation learning for heterogeneous dose-response curves estimation

Optimal experimental design for staggered rollouts

Federated causal inference in heterogeneous observational data

Target PCA: Transfer learning large dimensional panel data

Bias-variance tradeoffs for designing simultaneous temporal experiments

Stable estimation of heterogeneous treatment effects

Learning instrumental variable from data fusion for treatment effect estimation

Instrumental variables in causal inference and machine learning: A survey

Ruoxuan Xiong Information

University

Position

___

Citations(all)

850

Citations(since 2020)

822

Cited By

233

hIndex(all)

12

hIndex(since 2020)

12

i10Index(all)

12

i10Index(since 2020)

12

Email

University Profile Page

Google Scholar

Ruoxuan Xiong Skills & Research Interests

experimental design

causal inference

econometrics

Top articles of Ruoxuan Xiong

Contrastive balancing representation learning for heterogeneous dose-response curves estimation

Proceedings of the AAAI Conference on Artificial Intelligence

2024/3/24

Optimal experimental design for staggered rollouts

Management Science

2023/12/14

Federated causal inference in heterogeneous observational data

Statistics in Medicine

2023/10/30

Ruoxuan Xiong
Ruoxuan Xiong

H-Index: 8

Susan Athey
Susan Athey

H-Index: 49

Target PCA: Transfer learning large dimensional panel data

Journal of Econometrics

2023/10/11

Markus Pelger
Markus Pelger

H-Index: 9

Ruoxuan Xiong
Ruoxuan Xiong

H-Index: 8

Bias-variance tradeoffs for designing simultaneous temporal experiments

2023/7/25

Stable estimation of heterogeneous treatment effects

2023/7/3

Learning instrumental variable from data fusion for treatment effect estimation

Proceedings of the AAAI Conference on Artificial Intelligence

2023/6/26

Instrumental variables in causal inference and machine learning: A survey

arXiv preprint arXiv:2212.05778

2022/12/12

Interpretable sparse proximate factors for large dimensions

Journal of Business & Economic Statistics

2022/10/2

Markus Pelger
Markus Pelger

H-Index: 9

Ruoxuan Xiong
Ruoxuan Xiong

H-Index: 8

State-varying factor models of large dimensions

Journal of Business & Economic Statistics

2022/6/16

Markus Pelger
Markus Pelger

H-Index: 9

Ruoxuan Xiong
Ruoxuan Xiong

H-Index: 8

Large dimensional latent factor modeling with missing observations and applications to causal inference

Journal of Econometrics

2022/6/11

Ruoxuan Xiong
Ruoxuan Xiong

H-Index: 8

Markus Pelger
Markus Pelger

H-Index: 9

Ten rules for conducting retrospective pharmacoepidemiological analyses: Example COVID-19 study

Frontiers in Pharmacology

2021/7/28

Efficient treatment effect estimation in observational studies under heterogeneous partial interference

arXiv preprint arXiv:2107.12420

2021/7/26

Ruoxuan Xiong
Ruoxuan Xiong

H-Index: 8

Guido Imbens
Guido Imbens

H-Index: 65

Alpha-1 adrenergic receptor antagonists to prevent hyperinflammation and death from lower respiratory tract infection

Elife

2021/6/11

The association between alpha-1 adrenergic receptor antagonists and in-hospital mortality from COVID-19

Frontiers in Medicine

2021/3/31

Preventing cytokine storm syndrome in COVID-19 using α-1 adrenergic receptor antagonists

The Journal of clinical investigation

2020/7/1

Stable prediction with model misspecification and agnostic distribution shift

Proceedings of the AAAI Conference on Artificial Intelligence

2020/4/3

Essays on Statistical Learning and Causal Inference on Panel Data

2020

Ruoxuan Xiong
Ruoxuan Xiong

H-Index: 8

See List of Professors in Ruoxuan Xiong University(Stanford University)

Co-Authors

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